About Applied Intuition
Autonomy is one of the leading technological advances of this century that will come to impact our lives. The work you’ll do at Applied Intuition will meaningfully accelerate the efforts of the top autonomy teams in the world. At Applied Intuition, you will have a unique perspective on the development of cutting-edge technology while working with major players across the industry and the globe.
Applied Intuition provides software solutions to safely develop, test, and deploy autonomous vehicles at scale. The company’s suite of simulation, validation, and drive log management software enables development teams to create thousands of scenarios in minutes, run simulations at scale, and verify and validate algorithms for production deployment. Headquartered in Silicon Valley with offices in Detroit, Washington, D.C., Munich, Stockholm, Seoul, and Tokyo, Applied Intuition consists of software, robotics, and automotive experts with experiences from top global companies. Leading autonomy programs and 17 of the top 20 global OEMs use Applied Intuition’s solutions to bring autonomy to market faster.
About The Role
We are looking for a software engineer with expertise in perception for autonomous vehicles or mobile robots. Your contributions will focus on building out key capabilities of perception modules within an autonomous vehicle stack. You will also drive the design and development of computer vision and machine learning techniques to enable self-driving vehicles to navigate.
In addition to your engineering contributions, by working in our dynamic and customer-focused team culture, you will contribute to and learn from best practices in the nascent autonomy industry. We move fast and focus on excellence, for our products and for our business. If you are hands-on and looking for a place to have a multiplying effect on making autonomous systems a reality, Applied is the place for you!
We are hiring for all levels.
At Applied, you will:
- Design and implement capabilities and workflows for cutting-edge real-world perception systems
- Work closely with our sensor simulation team to ensure we build the best range of multi-fidelity simulation models
- Work closely with our infrastructure team to provide the best enterprise software for engineering, testing, and customer product teams
- Passion for turning their domain expertise into tooling that boosts the productivity of teams working on various real-world applications of autonomous systems
- 3+ years of experience building software components or (sub) systems that address real-world perception challenges
- Hands-on experience with more than one domain relevant software frameworks or tools, such as middleware, benchmarking suites, data sets and related pipelines, or algorithmic libraries
- Deep understanding of the concepts and methods behind any frameworks or libraries that they worked with
- Experience working with production level ML and DL perception algorithms for autonomous vehicles
- MSc or PhD in perception or closely related field
- Deep hands-on expertise in relevant algorithms or methods, such as non-linear optimization, computational geometry, numerical analysis, or distributed systems
- Experience building and shipping software frameworks or tools
Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
Applicants will be required to be fully vaccinated against COVID-19 upon commencing employment. Reasonable accommodations will be considered on a case-by-case basis for exemptions to this requirement in accordance with applicable federal and state law.
Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. #J-18808-Ljbffr